The limits of compliance can be inferred by the parametric method if the normality of the differences is indicated. or the use of non-parametric percentiles, if these assumptions are not included. Although the practical implementation of the exact Method of the Carkeet Interval  is well illustrated, the explanation of the differences between the exact and approximate methods has mainly focused on the relative sizes and symmetrical/asymmetrical limits of the resulting confidence limits. On the other hand, Bland-Altman`s 95% agreement limits are generally considered to be related to the measurement of compliance in comparing methods. Carkeet  and Carkeet and Goh  therefore focused on comparing approximate confidence intervals for the upper and lower limits of torque chords and tolerance intervals on both sides for normal distribution. Therefore, the particular benefit of precise interval procedures and the ability to limit approximate confidence intervals for each upper and lower limit of the Carkeet  and De Carkeet and Goh  agreement were not fully discussed. It is practical to conduct a detailed assessment of the accuracy and discrepancy between exact and approximate interval methods for an individual match limit in a multitude of model configurations. The problem of achieving a uniform confidence interval to cover both limitations of the agreement at the same time is more involved and an in-depth discussion on this subject goes beyond the scope of this study. A percentile is a numerical measure that represents the reference point below which a certain percentage of the target population values decreases.
Because of the conceptual simplicity and the uns contextal characteristic, percentiles are often used to determine the relative size and essential importance of quantitative measurements in all scientific fields. For example, children`s health conditions are often assessed on the basis of weight and height relative to national averages and national percentiles in growth charts. In addition, reference limits in medicine and related fields are widely applied to identify an informative amount of measurement from a reference population. The most typical reference limits are the central 95% of the interest population. As an important application, Bland and Altman`s compliance limits [1, 2] are composed of 95% of the 2.5th percentile and the 97.5th percentile for the distribution of the difference between the melted measurements. b) About 95% of patients have a difference in systolic blood pressure between the boundaries of concordance on the Bland-Altman plot A significant correlation was found between systolic blood pressure measured by the family physician and ambulatory systolic pressure during the day (r-0.46; P<0.05). Physician measurements exceeded the measurements obtained through outpatient monitoring by an average of 18.9 mm Hg. The Bland-Altman method was used to present the difference in systolic blood pressure for each patient (GP minus outpatient daily monitoring) with the average of both measures (fig. 1⇓).
Compliance limits are indicated by broken red lines, i.e. the two standard deviations of measurement differences on both sides of the average difference. Bland and Altman indicate that two measurement methods developed to measure the same parameter (or property) should have a good correlation when a group of samples is selected so that the property to be determined varies considerably.